Management of Paediatric Ulcerative Colitis, Part 2
Bibliographic record
Abstract
BACKGROUND AND AIM: Acute severe colitis (ASC) is one of the few emergencies in pediatric gastroenterology. Tight monitoring and timely medical and surgical interventions may improve outcomes and minimize morbidity and mortality. We aimed to standardize daily treatment of ASC in children through detailed recommendations and practice points which are based on a systematic review of the literature and consensus of experts. METHODS: These guidelines are a joint effort of the European Crohn's and Colitis Organization (ECCO) and the European Society of Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN). Fifteen predefined questions were addressed by working subgroups. An iterative consensus process, including 2 face-to-face meetings, was followed by voting of the national representatives of ECCO and all members of the Paediatric Inflammatory Bowel Disease (IBD) Porto group of ESPGHAN (43 voting experts). RESULTS: A total of 24 recommendations and 43 practice points were endorsed with a consensus rate of at least 91% regarding diagnosis, monitoring, and management of ASC in children. A summary flowchart is presented based on daily scoring of the Paediatric Ulcerative Colitis Activity Index. Several topics have been altered since the previous 2011 guidelines and from those published in adults. DISCUSSION: These guidelines standardize the management of ASC in children in an attempt to optimize outcomes of this intensive clinical scenario.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".